SHORT- AND LONG-RUN DEMAND AND SUBSTITUTION OF AGRICULTURAL INPUTS

Short- and long-run Hicksian and Marshallian elasticities are estimated, along with Morishima elasticities of substitution, using a restricted profit function and a series of decomposition equations. Convexity in prices and concavity in quasi-fixed factors of the restricted profit function are simultaneously imposed using Bayesian techniques. The empirical model is disaggregated in the input side, utilizes a Fuss-quadratic flexible functional form, incorporates the impact of agricultural policies, and introduces a new weather index. The methodology is applied to Illinois's agriculture, and implications for agriculture in the Corn Belt and the Northeast are briefly discussed.Demand and Price Analysis,

OFF-FARM WORK AND THE ECONOMIC IMPACT OF ADOPTING HERBICIDE-TOLERANT CROPS

This paper examines the hypothesis that farmers may be adopting herbicide-tolerant crops because of the simplicity and flexibility of weed control, freeing management time. We develop an econometric model to analyze the adoption of HT soybeans controlling for the effect of off-farm work and estimate it using 2000 survey data.Labor and Human Capital,

INNOVATION AND REGULATION IN THE PESTICIDE INDUSTRY

This paper examines the impact of pesticide regulation on the number of new pesticide registrations and pesticide toxicity. Results suggest that regulation adversely affects new pesticide introductions but encourages the development of pesticides with fewer toxic side effects. The estimated regression model implies that a 10% increase in regulatory costs (about $1.5 million per pesticide) causes a 5% reduction in the number of pesticides with higher toxicity.Agribusiness,

OFF-FARM WORK AND THE ADOPTION OF HERBICIDE-TOLERANT SOYBEANS

Adoption of herbicide-tolerant (HT) soybeans is proceeding rapidly despite little difference between the net returns to HT versus conventional soybeans. Using a multivariate probit model, we analyze the interaction of off-farm work and adoption and test if farmers adopt HT soybeans because its simplicity and flexibility frees management time.Biotechnology, herbicide-tolerant soybeans, technology adoption, off-farm work, household models, Crop Production/Industries,

Spatial Structures and Spatial Spillovers: A GME Approach

Spatial econometrics is a subdiscipline that have gained a huge popularity in the last twenty years, not only in theoretical econometrics but in empirical studies as well. Basically, spatial econometric methods measure spatial interaction and incorporate spatial structure into regression analysis. The specification of a matrix of spatial weights W plays a crucial role in the estimation of spatial models. The elements of this matrix measure the spatial relationships between two geographical locations i and j, and they are specified exogenously to the model. Several alternatives for W have been proposed in the literature, although binary matrices based on contiguity among locations or distance matrices are the most commons choices. One shortcoming of using this type of matrices for the spatial models is the impossibility of estimating “heterogeneous†spatial spillovers: the typical objective is the estimation of a parameter that measures the average spatial effect of the set of locations analysed. Roughly speaking, this is given by “ill-posed†econometric models where the number of (spatial) parameters to estimate is too large. In this paper, we explore the use of generalized maximum entropy econometrics (GME) to estimate spatial structures. This technique is very attractive in situations where one has to deal with estimation of “ill-posed†or “ill-conditioned†models. We compare by means of Monte Carlo simulations “classical†ML estimators with GME estimators in several situations with different availability of information.